Research topic
This topic collects papers that use machine-learning models or learning-based analysis for systems and software problems. The records identify the model, features, training data, baselines, evaluation metrics, and operational goal—such as anomaly detection, prediction, classification, or trace analysis.
Related search terms: machine learning systems analysis · learning-based performance analysis
23 papers in this topic, ordered newest first. The detailed paper records contain the evidence-grounded methods, tools, datasets, findings, and citation guidance.
2026 · ACM International Conference on the Foundations of Software Engineering (FSE) Companion
TraceSynth generates novel structured kernel-trace windows with a Transformer diffusion model and repairs generated events against invariants mined from real LTTng traces.
Keywords: kernel traces · trace generation · diffusion models · constraint-guided generation · LTTng
2025 · 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)
The paper implements a timestamp-aware multimodal video-retrieval pipeline that joins speech transcription, sampled-frame captioning, text embeddings, and approximate-nearest-neighbor search.
Keywords: video retrieval · semantic search · timestamp alignment · AI video search · ACDSA 2025
2025 · Authorea preprint
The preprint combines communication-related kernel/system-call events with distributed traces to detect communication performance anti-patterns in microservices.
Keywords: communication anti-patterns · DeathStarBench · LTTng · Trace Compass · Jaeger
2025 · 2025 IEEE International Conference on Collaborative Advances in Software and COmputiNg (CASCON)
The paper models LLM inference energy separately on CPU and GPU using hardware counters, device metrics, and task/model features, then compares classical and neural regressors across language tasks.
Keywords: LLM energy consumption · CPU energy · GPU energy · green AI · static metrics
2025 · AMCIS 2025, Data Science / SIG DSA (ERF)
The paper proposes the Triangle Multi-Dimensional Model for Bias Analysis, a hierarchical and interaction-based framework for tracing how bias originates, propagates, compounds, and feeds back across an LLM lifecycle.
Keywords: Triangle Multi-Dimensional Model · LLM bias · hierarchical bias analysis · cross-layer propagation · feedback loops
2025 · 2025 IEEE International Conference on Collaborative Advances in Software and COmputiNg (CASCON)
SynthLogAI benchmarks statistical, sequence, transformer, and prompt-based generative models for producing synthetic Linux logs while measuring fidelity, downstream utility, and privacy.
Keywords: synthetic Linux logs · generative AI · log generation · log evaluation · CASCON 2025
2024 · Software Impacts
The paper proposes a two-tier IoT intrusion detector that first separates normal from anomalous flows and then classifies the attack type with a CNN-BiLSTM model.
Keywords: IoT anomaly detection · CNN-BiLSTM · SMOTE · particle swarm optimization · PSO
2024 · ACM/SPEC International Conference on Performance Engineering (ICPE)
ALS uses source-code features and reinforcement learning to recommend which Python functions to log and which log levels to use for performance-bug diagnosis.
Keywords: adaptive logging · ALS · reinforcement learning · log placement · log level selection
2024 · 2024 IEEE International Conference on Big Data (BigData)
The paper evaluates whether software-energy predictors transfer across applications when they use hardware-performance and operating-system event representations rather than application-specific measurements alone.
Keywords: software energy consumption · predictive models · energy efficiency · software environments · IEEE Big Data 2024
2024 · 2024 ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE Companion)
The paper derives a 30-item taxonomy of log event characteristics that induce parsing errors and quantifies the characteristics with the largest impact across eight parsers.
Keywords: log parsing · log event characteristics · LEC taxonomy · LogHub · open coding
2024 · 2024 IEEE International Conference on Collaborative Advances in Software and COmputiNg (CASCON)
MemAdapt forecasts memory behavior under irregular sampling and uses the forecast to choose an adaptive monitoring rate that balances estimation quality with collection overhead.
Keywords: memory monitoring · irregular sampling · adaptive monitoring · time series · memory usage
2024 · ACL 2024 Main Conference
The paper introduces WinoVis, a multimodal benchmark and analysis framework for testing pronoun disambiguation in text-to-image models.
Keywords: Winograd Schema Challenge · WinoVis · text-to-image models · pronoun disambiguation · DAAM
2023 · ACM/IFIP/USENIX Middleware 2023 Industry Track
The paper applies a CNN-BiLSTM intrusion classifier to RPL/IoT traffic, combining convolutional feature extraction with bidirectional sequence modeling after imbalance-aware flow preprocessing.
Keywords: RPL attacks · IoT smart grid · CNN-BiLSTM · routing attacks · intrusion detection
2023 · 2023 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
EMD-SCS combines sequence prediction of system calls with sonification so that partial execution prefixes can support early malware detection and an interpretable auditory alert.
Keywords: malware detection · system-call sequences · sonification · Hamming distance · detection rate
2023 · ACM/SPEC ICPE Companion
The paper uses time-series analysis to identify and classify warmup, steady-state, and anomalous states in Java JMH microbenchmarks.
Keywords: Java Microbenchmark Harness · JMH · benchmark states · steady state · warmup
2023 · Companion of the 2023 ACM/SPEC International Conference on Performance Engineering (ICPE '23 Companion)
The study examines whether static source-code features are associated with the steady-state behavior of Java microbenchmarks during JVM warmup.
Keywords: Java Microbenchmark Harness · JMH · srcML · Lizard · Apriori
2023 · ACM/SPEC ICPE Companion
The paper uses sampled call graphs and machine learning to distinguish warmup from steady-state executions in Java microbenchmarks.
Keywords: Java · JMH · microbenchmarking · steady-state detection · warmup
2022 · ACM/IFIP/USENIX Middleware 2022 Demos/Posters
The poster proposes a hybrid IoT intrusion-detection pipeline with binary anomaly detection followed by multiclass attack classification.
Keywords: IoTID20 · RNN · SMOTE · PSO · binary classification
2021 · 2021 IEEE International Systems Conference (SysCon)
The paper combines LTTng system-call monitoring with recurrent and Transformer-style models for malware and anomalous system-behavior detection.
Keywords: malware detection · system-call analysis · LTTng · Trace Compass · LSTM
2021 · Journal of Hardware and Systems Security
The paper proposes a cloud-side anomaly detector that combines traffic, virtual-machine resource, and kernel-level indicators to identify several DDoS classes through change-point evidence.
Keywords: DDoS attacks · cloud environment · CUSUM · bandwidth exhaustion · application exhaustion
2020 · Journal of Cloud Computing
The paper combines host-level user/kernel tracing with machine learning to detect intrusion behavior on constrained IoT and home-automation systems.
Keywords: IoT intrusion detection · host-based IDS · LTTng · barectf · Common Trace Format
2019 · Journal of Hardware and Systems Security
The paper combines execution-trace and virtual-machine metrics with machine learning to detect EDoS behavior and restrict resource expansion to apparently normal VMs.
Keywords: Economic Denial of Sustainability · EDoS · DDoS · cloud computing · execution trace analysis
2010 · International Symposium on Information Management in a Changing World (IMCW 2010), Communications in Computer and Information Science 96
The paper combines automated Persian-news categorization with a web system for retrieving similar news items.
Keywords: Persian news · text categorization · document similarity · tf-idf · SVM